This page essentially gives an overview of the various splits already
tried when a user enters the model building phase after data annotation
and quality control steps.
Problem - This is the type of model you want to use for the model
building phase. It includes: Attribute prediction, Label class
prediction, Object detection, Image tag prediction, Instance
segmentation, Semantic segmentation.
Created by - This helps to track which user is experimenting with a particular model.
Images - This value gives an idea of the number of images (Total,
Train, Test, Validation) that were used for a particular set of
Experiments - Total number of experiments a user has carried out for a model type.